fine-tune-danh-gia-cam-xuc

This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4050
• Accuracy: 0.8970
• F1: 0.8972

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.3591	1.0	1287	0.3364	0.8815	0.8822
0.1426	2.0	2574	0.3404	0.8932	0.8936
0.4167	3.0	3861	0.4050	0.8970	0.8972

Framework versions

• Transformers 4.41.2
• Pytorch 2.7.1+cu126
• Datasets 4.0.0
• Tokenizers 0.19.1